{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "efeb897c",
   "metadata": {},
   "source": [
    "#  Thyroid Detection \n",
    "\n",
    "\n",
    "* Problem Statement\n",
    "\n",
    "    **  Thyroid disease is a common cause of medical diagnosis and prediction, with an onset\n",
    "        that is difficult to forecast in medical research. The thyroid gland is one of our body's\n",
    "        most vital organs. Thyroid hormone releases are responsible for metabolic regulation.\n",
    "        Hyperthyroidism and hypothyroidism are one of the two common diseases of the thyroidthat releases thyroid \n",
    "        hormones in       regulating the rate of body's metabolism.\n",
    "        The main goal is to predict the estimated risk on a patient's chance of obtaining thyroid  or not.\n",
    "\n",
    "age: int                  # age of the patient\n",
    "\n",
    "sex: str                  # sex patient identifies\n",
    "\n",
    "on_thyroxine: bool        # whether patient is on thyroxine\n",
    "\n",
    "query_on_thyroxine: bool  # whether patient is on thyroxine\n",
    "\n",
    "on_antithyroid_meds: bool # whether patient is on antithyroid meds\n",
    "\n",
    "sick: bool                # whether patient is sick\n",
    "\n",
    "pregnant: bool            # whether patient is pregnant\n",
    "\n",
    "thyroid_surgery: bool     # whether patient has undergone thyroid surgery\n",
    "\n",
    "I131_treatment: bool      # whether patient is undergoing I131 treatment\n",
    "\n",
    "query_hypothyroid: bool   # whether patient believes they have hypothyroid\n",
    "\n",
    "query_hyperthyroid: bool  # whether patient believes they have hyperthyroid\n",
    "\n",
    "lithium: bool             # whether patient has been treated with lithium\n",
    "\n",
    "goitre: bool              # whether patient has goitre\n",
    "\n",
    "tumor: bool               # whether patient has tumor\n",
    "\n",
    "hypopituitary: float      # whether patient has a hypopituitary gland\n",
    "\n",
    "psych: bool               # whether patient has a psych\n",
    "\n",
    "TSH_measured: bool        # whether TSH was measured in the blood\n",
    "\n",
    "TSH: float                # TSH level in blood from lab work\n",
    "\n",
    "T3_measured: bool         # whether T3 was measured in the blood\n",
    "\n",
    "T3: float                 # T3 level in blood from lab work\n",
    "\n",
    "TT4_measured: bool        # whether TT4 was measured in the blood\n",
    "\n",
    "TT4: float                # TT4 level in blood from lab work\n",
    "\n",
    "T4U_measured: bool        # whether T4U was measured in the blood\n",
    "\n",
    "T4U: float                # T4U level in blood from lab work\n",
    "\n",
    "FTI_measured: bool        # whether FTI was measured in the blood\n",
    "\n",
    "FTI: float                # FTI level in blood from lab work\n",
    "\n",
    "TBG_measured: bool        # whether TBG was measured in the blood\n",
    "\n",
    "TBG: float                # TBG level in blood from lab work\n",
    "\n",
    "referral_source: str      # referral source\n",
    "\n",
    "target: str               # hyperthyroidism medical diagnosis\n",
    "\n",
    "patient_id: str           # unique id of the patient\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "94f395b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.9.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import necessary libraries\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt \n",
    "%matplotlib inline \n",
    "\n",
    "import plotly \n",
    "import plotly.graph_objects as go\n",
    "import plotly.express as pe \n",
    "import plotly.offline as po\n",
    "from plotly.offline import init_notebook_mode\n",
    "import cufflinks as cf\n",
    "from plotly.offline import iplot\n",
    "cf.go_offline()\n",
    "\n",
    "from sklearn.impute import SimpleImputer,KNNImputer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import RobustScaler\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, classification_report,ConfusionMatrixDisplay,precision_score, recall_score, f1_score, roc_auc_score,roc_curve,confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90ffee1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This code imports necessary modules for statistical analysis.\n",
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.api import add_constant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ff2fcc92",
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotly.offline import iplot\n",
    "import plotly as py\n",
    "import plotly.tools as tls\n",
    "import cufflinks as cf  # Configuration file for plotly\n",
    "\n",
    "\n",
    "def configure_plotly_browser_state():\n",
    "\n",
    "    \"\"\"\n",
    "    Hides unnecessary plotly messages\n",
    "    \"\"\"\n",
    "    import IPython\n",
    "    display(IPython.core.display.HTML('''\n",
    "        \n",
    "        \n",
    "        '''))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2337121a",
   "metadata": {},
   "source": [
    "# READING DATASET "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dd7a1144",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"hypothyroid.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4d416707",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3772, 30)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code returns the shape of the dataframe\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5430bd7a",
   "metadata": {},
   "source": [
    "# TOP 5 RECORDS "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6b0c6b19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>on_thyroxine</th>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <th>sick</th>\n",
       "      <th>pregnant</th>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <th>I131_treatment</th>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <th>...</th>\n",
       "      <th>TT4_measured</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U_measured</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI_measured</th>\n",
       "      <th>FTI</th>\n",
       "      <th>TBG_measured</th>\n",
       "      <th>TBG</th>\n",
       "      <th>referral_source</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>125</td>\n",
       "      <td>t</td>\n",
       "      <td>1.14</td>\n",
       "      <td>t</td>\n",
       "      <td>109</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>SVHC</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>102</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>46</td>\n",
       "      <td>M</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>109</td>\n",
       "      <td>t</td>\n",
       "      <td>0.91</td>\n",
       "      <td>t</td>\n",
       "      <td>120</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>F</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>175</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>61</td>\n",
       "      <td>t</td>\n",
       "      <td>0.87</td>\n",
       "      <td>t</td>\n",
       "      <td>70</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>SVI</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  age sex on_thyroxine query_on_thyroxine on_antithyroid_medication sick  \\\n",
       "0  41   F            f                  f                         f    f   \n",
       "1  23   F            f                  f                         f    f   \n",
       "2  46   M            f                  f                         f    f   \n",
       "3  70   F            t                  f                         f    f   \n",
       "4  70   F            f                  f                         f    f   \n",
       "\n",
       "  pregnant thyroid_surgery I131_treatment query_hypothyroid  ... TT4_measured  \\\n",
       "0        f               f              f                 f  ...            t   \n",
       "1        f               f              f                 f  ...            t   \n",
       "2        f               f              f                 f  ...            t   \n",
       "3        f               f              f                 f  ...            t   \n",
       "4        f               f              f                 f  ...            t   \n",
       "\n",
       "   TT4 T4U_measured   T4U FTI_measured  FTI TBG_measured TBG referral_source  \\\n",
       "0  125            t  1.14            t  109            f   ?            SVHC   \n",
       "1  102            f     ?            f    ?            f   ?           other   \n",
       "2  109            t  0.91            t  120            f   ?           other   \n",
       "3  175            f     ?            f    ?            f   ?           other   \n",
       "4   61            t  0.87            t   70            f   ?             SVI   \n",
       "\n",
       "      Class  \n",
       "0  negative  \n",
       "1  negative  \n",
       "2  negative  \n",
       "3  negative  \n",
       "4  negative  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Prints the first few rows of a DataFrame\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f114e417",
   "metadata": {},
   "source": [
    "# BOTTOM 5 RECORDS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ae2285d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>on_thyroxine</th>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <th>sick</th>\n",
       "      <th>pregnant</th>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <th>I131_treatment</th>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <th>...</th>\n",
       "      <th>TT4_measured</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U_measured</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI_measured</th>\n",
       "      <th>FTI</th>\n",
       "      <th>TBG_measured</th>\n",
       "      <th>TBG</th>\n",
       "      <th>referral_source</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3767</th>\n",
       "      <td>30</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768</th>\n",
       "      <td>68</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>124</td>\n",
       "      <td>t</td>\n",
       "      <td>1.08</td>\n",
       "      <td>t</td>\n",
       "      <td>114</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>SVI</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3769</th>\n",
       "      <td>74</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>112</td>\n",
       "      <td>t</td>\n",
       "      <td>1.07</td>\n",
       "      <td>t</td>\n",
       "      <td>105</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3770</th>\n",
       "      <td>72</td>\n",
       "      <td>M</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>82</td>\n",
       "      <td>t</td>\n",
       "      <td>0.94</td>\n",
       "      <td>t</td>\n",
       "      <td>87</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>SVI</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3771</th>\n",
       "      <td>64</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>99</td>\n",
       "      <td>t</td>\n",
       "      <td>1.07</td>\n",
       "      <td>t</td>\n",
       "      <td>92</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     age sex on_thyroxine query_on_thyroxine on_antithyroid_medication sick  \\\n",
       "3767  30   F            f                  f                         f    f   \n",
       "3768  68   F            f                  f                         f    f   \n",
       "3769  74   F            f                  f                         f    f   \n",
       "3770  72   M            f                  f                         f    f   \n",
       "3771  64   F            f                  f                         f    f   \n",
       "\n",
       "     pregnant thyroid_surgery I131_treatment query_hypothyroid  ...  \\\n",
       "3767        f               f              f                 f  ...   \n",
       "3768        f               f              f                 f  ...   \n",
       "3769        f               f              f                 f  ...   \n",
       "3770        f               f              f                 f  ...   \n",
       "3771        f               f              f                 f  ...   \n",
       "\n",
       "     TT4_measured  TT4 T4U_measured   T4U FTI_measured  FTI TBG_measured TBG  \\\n",
       "3767            f    ?            f     ?            f    ?            f   ?   \n",
       "3768            t  124            t  1.08            t  114            f   ?   \n",
       "3769            t  112            t  1.07            t  105            f   ?   \n",
       "3770            t   82            t  0.94            t   87            f   ?   \n",
       "3771            t   99            t  1.07            t   92            f   ?   \n",
       "\n",
       "     referral_source     Class  \n",
       "3767           other  negative  \n",
       "3768             SVI  negative  \n",
       "3769           other  negative  \n",
       "3770             SVI  negative  \n",
       "3771           other  negative  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This command displays the last 5 rows of the data frame.\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5acf362",
   "metadata": {},
   "source": [
    "# Sample of Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5412831a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>on_thyroxine</th>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <th>sick</th>\n",
       "      <th>pregnant</th>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <th>I131_treatment</th>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <th>...</th>\n",
       "      <th>TT4_measured</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U_measured</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI_measured</th>\n",
       "      <th>FTI</th>\n",
       "      <th>TBG_measured</th>\n",
       "      <th>TBG</th>\n",
       "      <th>referral_source</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1167</th>\n",
       "      <td>68</td>\n",
       "      <td>M</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>81</td>\n",
       "      <td>t</td>\n",
       "      <td>1.01</td>\n",
       "      <td>t</td>\n",
       "      <td>81</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>compensated_hypothyroid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1644</th>\n",
       "      <td>62</td>\n",
       "      <td>F</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>103</td>\n",
       "      <td>t</td>\n",
       "      <td>1.12</td>\n",
       "      <td>t</td>\n",
       "      <td>93</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>74</td>\n",
       "      <td>M</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>77</td>\n",
       "      <td>t</td>\n",
       "      <td>0.91</td>\n",
       "      <td>t</td>\n",
       "      <td>84</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>SVI</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2899</th>\n",
       "      <td>40</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>78</td>\n",
       "      <td>t</td>\n",
       "      <td>0.9</td>\n",
       "      <td>t</td>\n",
       "      <td>87</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>compensated_hypothyroid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2121</th>\n",
       "      <td>72</td>\n",
       "      <td>F</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>t</td>\n",
       "      <td>164</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>f</td>\n",
       "      <td>?</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     age sex on_thyroxine query_on_thyroxine on_antithyroid_medication sick  \\\n",
       "1167  68   M            f                  f                         f    f   \n",
       "1644  62   F            t                  f                         f    f   \n",
       "63    74   M            f                  f                         f    f   \n",
       "2899  40   ?            f                  f                         f    f   \n",
       "2121  72   F            t                  f                         f    f   \n",
       "\n",
       "     pregnant thyroid_surgery I131_treatment query_hypothyroid  ...  \\\n",
       "1167        f               f              f                 f  ...   \n",
       "1644        f               f              f                 f  ...   \n",
       "63          f               f              f                 f  ...   \n",
       "2899        f               f              f                 f  ...   \n",
       "2121        f               f              f                 f  ...   \n",
       "\n",
       "     TT4_measured  TT4 T4U_measured   T4U FTI_measured FTI TBG_measured TBG  \\\n",
       "1167            t   81            t  1.01            t  81            f   ?   \n",
       "1644            t  103            t  1.12            t  93            f   ?   \n",
       "63              t   77            t  0.91            t  84            f   ?   \n",
       "2899            t   78            t   0.9            t  87            f   ?   \n",
       "2121            t  164            f     ?            f   ?            f   ?   \n",
       "\n",
       "     referral_source                    Class  \n",
       "1167           other  compensated_hypothyroid  \n",
       "1644           other                 negative  \n",
       "63               SVI                 negative  \n",
       "2899           other  compensated_hypothyroid  \n",
       "2121           other                 negative  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code will randomly sample 5 rows from the dataframe df and display them\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "47aeb2ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "negative                   3481\n",
       "compensated_hypothyroid     194\n",
       "primary_hypothyroid          95\n",
       "secondary_hypothyroid         2\n",
       "Name: Class, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code counts the number of occurrences of each value in the 'Class' column of the df dataframe.\n",
    "df['Class'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00c5dc45",
   "metadata": {},
   "source": [
    "# SHAPE OF DATA SET "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8aabcd98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3772, 30)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2f0de75",
   "metadata": {},
   "source": [
    "# CHECKING DUPLICATES "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0837c335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code counts the number of duplicate rows in a Pandas DataFrame\n",
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad6bfbe8",
   "metadata": {},
   "source": [
    "# DROPPING DUPLICATES "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "40d0711e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove duplicate rows from the dataframe\n",
    "df = df.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3efe8eea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6091673",
   "metadata": {},
   "source": [
    "# CHECKING NULLS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c85b44ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age                          0\n",
       "sex                          0\n",
       "on_thyroxine                 0\n",
       "query_on_thyroxine           0\n",
       "on_antithyroid_medication    0\n",
       "sick                         0\n",
       "pregnant                     0\n",
       "thyroid_surgery              0\n",
       "I131_treatment               0\n",
       "query_hypothyroid            0\n",
       "query_hyperthyroid           0\n",
       "lithium                      0\n",
       "goitre                       0\n",
       "tumor                        0\n",
       "hypopituitary                0\n",
       "psych                        0\n",
       "TSH_measured                 0\n",
       "TSH                          0\n",
       "T3_measured                  0\n",
       "T3                           0\n",
       "TT4_measured                 0\n",
       "TT4                          0\n",
       "T4U_measured                 0\n",
       "T4U                          0\n",
       "FTI_measured                 0\n",
       "FTI                          0\n",
       "TBG_measured                 0\n",
       "TBG                          0\n",
       "referral_source              0\n",
       "Class                        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code uses the isna() function to check for null values in a dataframe and returns the sum of them.\n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5b1addee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "age 1\n",
      "sex 149\n",
      "TSH 309\n",
      "T3 709\n",
      "TT4 171\n",
      "T4U 327\n",
      "FTI 325\n",
      "TBG 3711\n"
     ]
    }
   ],
   "source": [
    "for column in df.columns:\n",
    "    # Count the number of missing values represented by '?'\n",
    "    count = df[column][df[column] == '?'].count()\n",
    "    # If missing values are found, print the column name and count\n",
    "    if count != 0:\n",
    "        print(column, count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9e139746",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the 'TBG' column as it contains all missing values\n",
    "df = df.drop('TBG', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7f8fd4ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'on_thyroxine', 'query_on_thyroxine',\n",
       "       'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery',\n",
       "       'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium',\n",
       "       'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH_measured', 'TSH',\n",
       "       'T3_measured', 'T3', 'TT4_measured', 'TT4', 'T4U_measured', 'T4U',\n",
       "       'FTI_measured', 'FTI', 'TBG_measured', 'referral_source', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1c96e3ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3711, 29)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db72bd7",
   "metadata": {},
   "source": [
    "# Numerical and Categorical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "498f6856",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We have 0 numerical features : []\n",
      "\n",
      "We have 29 categorical features : ['age', 'sex', 'on_thyroxine', 'query_on_thyroxine', 'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery', 'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium', 'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH_measured', 'TSH', 'T3_measured', 'T3', 'TT4_measured', 'TT4', 'T4U_measured', 'T4U', 'FTI_measured', 'FTI', 'TBG_measured', 'referral_source', 'Class']\n"
     ]
    }
   ],
   "source": [
    "numeric_features = [feature for feature in df.columns if df[feature].dtype != 'O']\n",
    "categorical_features = [feature for feature in df.columns if df[feature].dtype == 'O']\n",
    "# print columns\n",
    "print('We have {} numerical features : {}'.format(len(numeric_features), numeric_features))\n",
    "print('\\nWe have {} categorical features : {}'.format(len(categorical_features), categorical_features))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "77c70ce2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 3711 entries, 0 to 3771\n",
      "Data columns (total 29 columns):\n",
      " #   Column                     Non-Null Count  Dtype \n",
      "---  ------                     --------------  ----- \n",
      " 0   age                        3711 non-null   object\n",
      " 1   sex                        3711 non-null   object\n",
      " 2   on_thyroxine               3711 non-null   object\n",
      " 3   query_on_thyroxine         3711 non-null   object\n",
      " 4   on_antithyroid_medication  3711 non-null   object\n",
      " 5   sick                       3711 non-null   object\n",
      " 6   pregnant                   3711 non-null   object\n",
      " 7   thyroid_surgery            3711 non-null   object\n",
      " 8   I131_treatment             3711 non-null   object\n",
      " 9   query_hypothyroid          3711 non-null   object\n",
      " 10  query_hyperthyroid         3711 non-null   object\n",
      " 11  lithium                    3711 non-null   object\n",
      " 12  goitre                     3711 non-null   object\n",
      " 13  tumor                      3711 non-null   object\n",
      " 14  hypopituitary              3711 non-null   object\n",
      " 15  psych                      3711 non-null   object\n",
      " 16  TSH_measured               3711 non-null   object\n",
      " 17  TSH                        3711 non-null   object\n",
      " 18  T3_measured                3711 non-null   object\n",
      " 19  T3                         3711 non-null   object\n",
      " 20  TT4_measured               3711 non-null   object\n",
      " 21  TT4                        3711 non-null   object\n",
      " 22  T4U_measured               3711 non-null   object\n",
      " 23  T4U                        3711 non-null   object\n",
      " 24  FTI_measured               3711 non-null   object\n",
      " 25  FTI                        3711 non-null   object\n",
      " 26  TBG_measured               3711 non-null   object\n",
      " 27  referral_source            3711 non-null   object\n",
      " 28  Class                      3711 non-null   object\n",
      "dtypes: object(29)\n",
      "memory usage: 869.8+ KB\n"
     ]
    }
   ],
   "source": [
    "#finding dataytypes of each features\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "58f7f0ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>3711</td>\n",
       "      <td>94</td>\n",
       "      <td>59</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <td>3711</td>\n",
       "      <td>3</td>\n",
       "      <td>F</td>\n",
       "      <td>2424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>on_thyroxine</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sick</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pregnant</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I131_treatment</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>query_hyperthyroid</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lithium</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>goitre</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tumor</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypopituitary</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>psych</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>3527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>3402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH</th>\n",
       "      <td>3711</td>\n",
       "      <td>288</td>\n",
       "      <td>?</td>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3</th>\n",
       "      <td>3711</td>\n",
       "      <td>70</td>\n",
       "      <td>?</td>\n",
       "      <td>709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TT4_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>3540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TT4</th>\n",
       "      <td>3711</td>\n",
       "      <td>242</td>\n",
       "      <td>?</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4U_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>3384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4U</th>\n",
       "      <td>3711</td>\n",
       "      <td>147</td>\n",
       "      <td>?</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FTI_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>3386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FTI</th>\n",
       "      <td>3711</td>\n",
       "      <td>235</td>\n",
       "      <td>?</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBG_measured</th>\n",
       "      <td>3711</td>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>3711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>referral_source</th>\n",
       "      <td>3711</td>\n",
       "      <td>5</td>\n",
       "      <td>other</td>\n",
       "      <td>2140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Class</th>\n",
       "      <td>3711</td>\n",
       "      <td>4</td>\n",
       "      <td>negative</td>\n",
       "      <td>3420</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          count unique       top  freq\n",
       "age                        3711     94        59    95\n",
       "sex                        3711      3         F  2424\n",
       "on_thyroxine               3711      2         f  3247\n",
       "query_on_thyroxine         3711      2         f  3661\n",
       "on_antithyroid_medication  3711      2         f  3669\n",
       "sick                       3711      2         f  3564\n",
       "pregnant                   3711      2         f  3658\n",
       "thyroid_surgery            3711      2         f  3658\n",
       "I131_treatment             3711      2         f  3652\n",
       "query_hypothyroid          3711      2         f  3477\n",
       "query_hyperthyroid         3711      2         f  3477\n",
       "lithium                    3711      2         f  3693\n",
       "goitre                     3711      2         f  3677\n",
       "tumor                      3711      2         f  3615\n",
       "hypopituitary              3711      2         f  3710\n",
       "psych                      3711      2         f  3527\n",
       "TSH_measured               3711      2         t  3402\n",
       "TSH                        3711    288         ?   309\n",
       "T3_measured                3711      2         t  3002\n",
       "T3                         3711     70         ?   709\n",
       "TT4_measured               3711      2         t  3540\n",
       "TT4                        3711    242         ?   171\n",
       "T4U_measured               3711      2         t  3384\n",
       "T4U                        3711    147         ?   327\n",
       "FTI_measured               3711      2         t  3386\n",
       "FTI                        3711    235         ?   325\n",
       "TBG_measured               3711      1         f  3711\n",
       "referral_source            3711      5     other  2140\n",
       "Class                      3711      4  negative  3420"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7acd8656",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2a6c0ad8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1991"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#filling missing dat ain the form of ? by np.nan values \n",
    "df.isin(['?']).sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17e1d855",
   "metadata": {},
   "source": [
    "Overall 1991 values are missing in the form of ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "788fdeae",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.replace('?',np.nan,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "24006f69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3711, 29)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8578a791",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'on_thyroxine', 'query_on_thyroxine',\n",
       "       'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery',\n",
       "       'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium',\n",
       "       'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH_measured', 'TSH',\n",
       "       'T3_measured', 'T3', 'TT4_measured', 'TT4', 'T4U_measured', 'T4U',\n",
       "       'FTI_measured', 'FTI', 'TBG_measured', 'referral_source', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50fda99a",
   "metadata": {},
   "source": [
    "# Replacing age datatype into numerical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1897b3fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['age'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7199dd36",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age']=pd.to_numeric(df['age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b8e1c82d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sex',\n",
       " 'on_thyroxine',\n",
       " 'query_on_thyroxine',\n",
       " 'on_antithyroid_medication',\n",
       " 'sick',\n",
       " 'pregnant',\n",
       " 'thyroid_surgery',\n",
       " 'I131_treatment',\n",
       " 'query_hypothyroid',\n",
       " 'query_hyperthyroid',\n",
       " 'lithium',\n",
       " 'goitre',\n",
       " 'tumor',\n",
       " 'hypopituitary',\n",
       " 'psych',\n",
       " 'TSH_measured',\n",
       " 'TSH',\n",
       " 'T3_measured',\n",
       " 'T3',\n",
       " 'TT4_measured',\n",
       " 'TT4',\n",
       " 'T4U_measured',\n",
       " 'T4U',\n",
       " 'FTI_measured',\n",
       " 'FTI',\n",
       " 'TBG_measured',\n",
       " 'referral_source',\n",
       " 'Class']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical = [i for i in df.columns if df[i].dtype == 'O']\n",
    "categorical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e495e59a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy=df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ee2eb66a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1.3\n",
       "1        4.1\n",
       "2       0.98\n",
       "3       0.16\n",
       "4       0.72\n",
       "        ... \n",
       "3767     NaN\n",
       "3768       1\n",
       "3769     5.1\n",
       "3770     0.7\n",
       "3771       1\n",
       "Name: TSH, Length: 3711, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['TSH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a3716edc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert the TSH into numeric \n",
    "df_copy['TSH']=df_copy['TSH'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d2bcebd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['T3'].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2bdc5ec7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       2.5\n",
       "1         2\n",
       "2       NaN\n",
       "3       1.9\n",
       "4       1.2\n",
       "       ... \n",
       "3767    NaN\n",
       "3768    2.1\n",
       "3769    1.8\n",
       "3770      2\n",
       "3771    2.2\n",
       "Name: T3, Length: 3711, dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['T3']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "5b18eb27",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert the T3 into numeric \n",
    "df_copy['T3']=df_copy['T3'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "85a6c428",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['TT4'].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5af77c82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       125\n",
       "1       102\n",
       "2       109\n",
       "3       175\n",
       "4        61\n",
       "       ... \n",
       "3767    NaN\n",
       "3768    124\n",
       "3769    112\n",
       "3770     82\n",
       "3771     99\n",
       "Name: TT4, Length: 3711, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['TT4']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0aebf6c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Converting TT4 to numric format \n",
    "df_copy['TT4']=df_copy['TT4'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "e6f23939",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['T4U'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "38081e4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1.14\n",
       "1        NaN\n",
       "2       0.91\n",
       "3        NaN\n",
       "4       0.87\n",
       "        ... \n",
       "3767     NaN\n",
       "3768    1.08\n",
       "3769    1.07\n",
       "3770    0.94\n",
       "3771    1.07\n",
       "Name: T4U, Length: 3711, dtype: object"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['T4U']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "3946aba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy['T4U']=df_copy['T4U'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a5575f99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['FTI'].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "338b9230",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       109\n",
       "1       NaN\n",
       "2       120\n",
       "3       NaN\n",
       "4        70\n",
       "       ... \n",
       "3767    NaN\n",
       "3768    114\n",
       "3769    105\n",
       "3770     87\n",
       "3771     92\n",
       "Name: FTI, Length: 3711, dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['FTI']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1df32a46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['109', nan, '120', '70', '141', '78', '115', '132', '93', '121',\n",
       "       '153', '151', '107', '119', '87', '81', '104', '130', '106', '116',\n",
       "       '131', '190', '92', '102', '76', '98', '90', '61', '94', '129',\n",
       "       '95', '91', '33', '113', '148', '140', '171', '155', '186', '122',\n",
       "       '136', '110', '111', '97', '72', '100', '88', '67', '84', '103',\n",
       "       '135', '203', '112', '117', '180', '142', '145', '156', '96',\n",
       "       '134', '8.9', '60', '139', '41', '99', '89', '146', '124', '105',\n",
       "       '85', '157', '143', '71', '221', '28', '108', '137', '83', '74',\n",
       "       '170', '65', '101', '127', '274', '154', '114', '62', '86', '126',\n",
       "       '125', '64', '172', '162', '79', '118', '73', '152', '163', '149',\n",
       "       '14', '51', '165', '77', '32', '69', '80', '11', '54', '164',\n",
       "       '123', '144', '10', '214', '200', '160', '53', '16', '138', '169',\n",
       "       '56', '47', '133', '43', '68', '179', '224', '220', '82', '362',\n",
       "       '182', '75', '66', '161', '57', '58', '312', '63', '128', '147',\n",
       "       '158', '281', '207', '216', '251', '194', '46', '7', '42', '174',\n",
       "       '395', '185', '13', '201', '48', '173', '167', '188', '150', '235',\n",
       "       '175', '159', '5.4', '189', '59', '166', '34', '228', '232', '217',\n",
       "       '177', '176', '195', '219', '17', '210', '168', '205', '39', '187',\n",
       "       '50', '349', '52', '206', '253', '242', '244', '213', '178', '247',\n",
       "       '215', '198', '19', '237', '37', '7.6', '24', '2', '3', '191',\n",
       "       '223', '9', '29', '222', '204', '26', '218', '197', '49', '209',\n",
       "       '183', '265', '199', '196', '20', '283', '36', '249', '181', '8.4',\n",
       "       '291', '55', '245', '18', '40', '8.5', '184', '4', '21', '280',\n",
       "       '2.8', '9.1', '27', '15', '35', '227'], dtype=object)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['FTI'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "107dc6f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy['FTI']=df_copy['FTI'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "d7d1431b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>TSH</th>\n",
       "      <th>T3</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3710.000000</td>\n",
       "      <td>3402.000000</td>\n",
       "      <td>3002.000000</td>\n",
       "      <td>3540.000000</td>\n",
       "      <td>3384.000000</td>\n",
       "      <td>3386.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>51.860377</td>\n",
       "      <td>5.087820</td>\n",
       "      <td>2.013504</td>\n",
       "      <td>108.328475</td>\n",
       "      <td>0.994989</td>\n",
       "      <td>110.480715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>20.123585</td>\n",
       "      <td>24.524998</td>\n",
       "      <td>0.827572</td>\n",
       "      <td>35.605132</td>\n",
       "      <td>0.195485</td>\n",
       "      <td>33.088316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.005000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>93.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>54.000000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>103.000000</td>\n",
       "      <td>0.980000</td>\n",
       "      <td>107.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>67.000000</td>\n",
       "      <td>2.700000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>124.000000</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>124.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>455.000000</td>\n",
       "      <td>530.000000</td>\n",
       "      <td>10.600000</td>\n",
       "      <td>430.000000</td>\n",
       "      <td>2.320000</td>\n",
       "      <td>395.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age          TSH           T3          TT4          T4U  \\\n",
       "count  3710.000000  3402.000000  3002.000000  3540.000000  3384.000000   \n",
       "mean     51.860377     5.087820     2.013504   108.328475     0.994989   \n",
       "std      20.123585    24.524998     0.827572    35.605132     0.195485   \n",
       "min       1.000000     0.005000     0.050000     2.000000     0.250000   \n",
       "25%      36.000000     0.500000     1.600000    88.000000     0.880000   \n",
       "50%      54.000000     1.400000     2.000000   103.000000     0.980000   \n",
       "75%      67.000000     2.700000     2.400000   124.000000     1.080000   \n",
       "max     455.000000   530.000000    10.600000   430.000000     2.320000   \n",
       "\n",
       "               FTI  \n",
       "count  3386.000000  \n",
       "mean    110.480715  \n",
       "std      33.088316  \n",
       "min       2.000000  \n",
       "25%      93.000000  \n",
       "50%     107.000000  \n",
       "75%     124.000000  \n",
       "max     395.000000  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a71bba6c",
   "metadata": {},
   "source": [
    "Observation : It is shown max age of patient is noted 455 it cant be correct so it is wrong data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da8012d4",
   "metadata": {},
   "source": [
    "# Removing More Redundant Columns from Dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "323b79d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Since actual values are present in TSH, T3, TT4, T4U FTI so their measured values are not significant \n",
    "# for prediction of thyroid disease so we can remove them \n",
    "columns_to_drop = ['TSH_measured', 'T3_measured', 'TT4_measured', 'T4U_measured', 'FTI_measured', 'TBG_measured']\n",
    "df_copy.drop(columns=columns_to_drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e687036",
   "metadata": {},
   "source": [
    "# Chekcking missing data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "b2201e21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "T3                           709\n",
       "T4U                          327\n",
       "FTI                          325\n",
       "TSH                          309\n",
       "TT4                          171\n",
       "sex                          149\n",
       "age                            1\n",
       "goitre                         0\n",
       "referral_source                0\n",
       "psych                          0\n",
       "hypopituitary                  0\n",
       "tumor                          0\n",
       "lithium                        0\n",
       "query_hyperthyroid             0\n",
       "query_hypothyroid              0\n",
       "I131_treatment                 0\n",
       "thyroid_surgery                0\n",
       "pregnant                       0\n",
       "sick                           0\n",
       "on_antithyroid_medication      0\n",
       "query_on_thyroxine             0\n",
       "on_thyroxine                   0\n",
       "Class                          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.isna().sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "634074d5",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5678efaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "negative                   3420\n",
       "compensated_hypothyroid     194\n",
       "primary_hypothyroid          95\n",
       "secondary_hypothyroid         2\n",
       "Name: Class, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['Class'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "52aa92f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Ckecking the distribution of target variable \n",
    "class_count=df_copy['Class'].value_counts().to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "ae29d624",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "type": "bar",
         "x": [
          "negative",
          "compensated_hypothyroid",
          "primary_hypothyroid",
          "secondary_hypothyroid"
         ],
         "y": [
          3420,
          194,
          95,
          2
         ]
        }
       ],
       "layout": {
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Distribution of Target Variable"
        },
        "xaxis": {
         "title": {
          "text": "Class"
         }
        },
        "yaxis": {
         "title": {
          "text": "Count"
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"51bdcd0c-7dac-4599-8ebf-6fbf4906b112\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"51bdcd0c-7dac-4599-8ebf-6fbf4906b112\")) {                    Plotly.newPlot(                        \"51bdcd0c-7dac-4599-8ebf-6fbf4906b112\",                        [{\"x\":[\"negative\",\"compensated_hypothyroid\",\"primary_hypothyroid\",\"secondary_hypothyroid\"],\"y\":[3420,194,95,2],\"type\":\"bar\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"text\":\"Distribution of Target Variable\"},\"xaxis\":{\"title\":{\"text\":\"Class\"}},\"yaxis\":{\"title\":{\"text\":\"Count\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('51bdcd0c-7dac-4599-8ebf-6fbf4906b112');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = go.Figure(data=[go.Bar(x=list(class_count.keys()), y=list(class_count.values()))])\n",
    "fig.update_layout(title='Distribution of Target Variable',\n",
    "                  xaxis_title='Class',\n",
    "                  yaxis_title='Count')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f114ccb",
   "metadata": {},
   "source": [
    "# lets see the distribution of age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "2b8f8bd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='age', ylabel='Density'>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df_copy['age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "9a7ac728",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning:\n",
      "\n",
      "Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='age'>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(df_copy['age'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97af87ff",
   "metadata": {},
   "source": [
    "# Lets see the distribution of Sex feature "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ed63fceb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          2424,
          1138
         ]
        }
       ],
       "layout": {
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Distribution Female and Males "
        },
        "xaxis": {
         "title": {
          "text": "Gender"
         }
        },
        "yaxis": {
         "title": {
          "text": "Count"
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"dd2e2156-bd64-4c68-a603-3b28b5e4fcb0\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"dd2e2156-bd64-4c68-a603-3b28b5e4fcb0\")) {                    Plotly.newPlot(                        \"dd2e2156-bd64-4c68-a603-3b28b5e4fcb0\",                        [{\"x\":[\"F\",\"M\"],\"y\":[2424,1138],\"type\":\"bar\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"text\":\"Distribution Female and Males \"},\"xaxis\":{\"title\":{\"text\":\"Gender\"}},\"yaxis\":{\"title\":{\"text\":\"Count\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('dd2e2156-bd64-4c68-a603-3b28b5e4fcb0');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sex_counts=df_copy['sex'].value_counts().to_dict()\n",
    "fig = go.Figure(data=[go.Bar(x=list(sex_counts.keys()), y=list(sex_counts.values()))])\n",
    "fig.update_layout(title='Distribution Female and Males ',\n",
    "                  xaxis_title='Gender',\n",
    "                  yaxis_title='Count')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "f681d62e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Observation : from overall dataset female has highest distribution compared to male"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "7e4fac26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "compensated_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          145,
          42
         ]
        },
        {
         "marker": {
          "color": "rgba(55, 128, 191, 0.6)",
          "line": {
           "color": "rgba(55, 128, 191, 1.0)",
           "width": 1
          }
         },
         "name": "negative",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          2209,
          1073
         ]
        },
        {
         "marker": {
          "color": "rgba(50, 171, 96, 0.6)",
          "line": {
           "color": "rgba(50, 171, 96, 1.0)",
           "width": 1
          }
         },
         "name": "primary_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          69,
          22
         ]
        },
        {
         "marker": {
          "color": "rgba(128, 0, 128, 0.6)",
          "line": {
           "color": "rgba(128, 0, 128, 1.0)",
           "width": 1
          }
         },
         "name": "secondary_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          1,
          1
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"09b9acc8-7a67-439d-861d-dac3c4ec6b6e\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"09b9acc8-7a67-439d-861d-dac3c4ec6b6e\")) {                    Plotly.newPlot(                        \"09b9acc8-7a67-439d-861d-dac3c4ec6b6e\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"compensated_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[145,42],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(55, 128, 191, 0.6)\",\"line\":{\"color\":\"rgba(55, 128, 191, 1.0)\",\"width\":1}},\"name\":\"negative\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[2209,1073],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(50, 171, 96, 0.6)\",\"line\":{\"color\":\"rgba(50, 171, 96, 1.0)\",\"width\":1}},\"name\":\"primary_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[69,22],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(128, 0, 128, 0.6)\",\"line\":{\"color\":\"rgba(128, 0, 128, 1.0)\",\"width\":1}},\"name\":\"secondary_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[1,1],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('09b9acc8-7a67-439d-861d-dac3c4ec6b6e');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df_copy['sex'],df['Class']).iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "522c19de",
   "metadata": {},
   "source": [
    "Observation mostly feamle are free from thyroid disease "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40a7a882",
   "metadata": {},
   "source": [
    "# Analysis of on_thyroxine and query_on_thyroxine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02e10fe0",
   "metadata": {},
   "source": [
    "In medical terms, levothyroxine is a medication used to treat an underactive thyroid gland (hypothyroidism). It is a synthetic form of the thyroid hormone thyroxine, also known as T4. \"On_thyroxine\" refers to whether a patient is currently taking levothyroxine medication, while \"query_on_thyroxine\" indicates whether there is uncertainty about whether the patient is taking levothyroxine or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "3c8e41c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "f    3247\n",
       "t     464\n",
       "Name: on_thyroxine, dtype: int64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['on_thyroxine'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "1427346d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "on_thyroxine",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          3247,
          464
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"900d6bad-fb12-489f-b8cb-5a993efd2b54\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"900d6bad-fb12-489f-b8cb-5a993efd2b54\")) {                    Plotly.newPlot(                        \"900d6bad-fb12-489f-b8cb-5a993efd2b54\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"on_thyroxine\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[3247,464],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('900d6bad-fb12-489f-b8cb-5a993efd2b54');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_copy['on_thyroxine'].value_counts().iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "341c7607",
   "metadata": {},
   "source": [
    "#Observation : 464 people  are taking levothyroxine  and 3247 are not taking levothyroxine but it not only case we have to check their imact with TSH level it it high with people taking levothyroxine  their metabolism has to be adjusted but if they are not taking levothyroxine  and if their TSH level is high people has to start their treatment with T4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "7d7b757f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "f",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          2061,
          1052
         ]
        },
        {
         "marker": {
          "color": "rgba(55, 128, 191, 0.6)",
          "line": {
           "color": "rgba(55, 128, 191, 1.0)",
           "width": 1
          }
         },
         "name": "t",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          363,
          86
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"c05056b9-a7d9-4993-828d-87a35c3fccc9\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"c05056b9-a7d9-4993-828d-87a35c3fccc9\")) {                    Plotly.newPlot(                        \"c05056b9-a7d9-4993-828d-87a35c3fccc9\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"f\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[2061,1052],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(55, 128, 191, 0.6)\",\"line\":{\"color\":\"rgba(55, 128, 191, 1.0)\",\"width\":1}},\"name\":\"t\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[363,86],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('c05056b9-a7d9-4993-828d-87a35c3fccc9');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df_copy['sex'],df_copy['on_thyroxine']).iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d49bce81",
   "metadata": {},
   "source": [
    "Obseravtion : As compared to Male Female are more in number who are taking medication to treat hypothyroid disease"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ab30aba",
   "metadata": {},
   "source": [
    "# Checking analysis of query_on_thyroxine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcfbed6d",
   "metadata": {},
   "source": [
    "\"Query_on_thyroxine\" is a medical term used in cases of thyroid function testing. It refers to the presence or absence of thyroid hormone replacement therapy in a patient at the time of testing.\n",
    "\n",
    "Thyroxine is a thyroid hormone that plays a crucial role in regulating metabolism, growth, and development. When the thyroid gland does not produce enough thyroxine, a condition known as hypothyroidism, hormone replacement therapy may be prescribed to supplement the body's thyroxine levels.\n",
    "\n",
    "In cases where a patient is already taking thyroxine replacement therapy, their thyroid function testing results may be affected. Therefore, it is essential to note whether a patient is currently taking thyroxine or not when interpreting thyroid function tests."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "d4539d7d",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "query_on_thyroxine",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          3661,
          50
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"cb4baf70-470e-47e8-9071-a888b3b351aa\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"cb4baf70-470e-47e8-9071-a888b3b351aa\")) {                    Plotly.newPlot(                        \"cb4baf70-470e-47e8-9071-a888b3b351aa\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"query_on_thyroxine\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[3661,50],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('cb4baf70-470e-47e8-9071-a888b3b351aa');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_copy['query_on_thyroxine'].value_counts().iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec460e79",
   "metadata": {},
   "source": [
    "Obeservation: 50 people are taking thyroxine replacement therapy, so while testing their thyroid test it must be noted that they are already taking thyroxine replacement therapy,"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8874d53",
   "metadata": {},
   "source": [
    "# Analysis of on_antithyroid_medication\n",
    "\n",
    " * Antithyroid medication is commonly used in the treatment of hyperthyroidism, which is a condition characterized by an overactive thyroid gland. In cases where the patient is on antithyroid medication, the medication can affect the results of thyroid function tests, which are used to diagnose and monitor thyroid function.\n",
    " \n",
    " * Antithyroid medication can affect these test results by reducing the levels of thyroid hormones in the blood.\n",
    " \n",
    " * The significance of antithyroid medication in thyroid detection cases is that it can complicate the interpretation of thyroid function test results\n",
    " \n",
    " * "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "44b11457",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "on_antithyroid_medication",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          3669,
          42
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"88a45abc-2d93-45f4-95cb-f8b17f0ba5b3\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"88a45abc-2d93-45f4-95cb-f8b17f0ba5b3\")) {                    Plotly.newPlot(                        \"88a45abc-2d93-45f4-95cb-f8b17f0ba5b3\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"on_antithyroid_medication\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[3669,42],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('88a45abc-2d93-45f4-95cb-f8b17f0ba5b3');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_copy['on_antithyroid_medication'].value_counts().iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2180eac3",
   "metadata": {},
   "source": [
    "Obseravtion : from overall patients 42 are taking antithyroid medication it seems they may be patients of hyperthyrodism"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d9b901a",
   "metadata": {},
   "source": [
    "# Effect of Pregnanacy over Thyroid "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "bb211176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 1, 2, 3],\n",
       " [Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, '')])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.histplot(binwidth=0.5, x=\"Class\", hue=\"pregnant\", data=df_copy,stat=\"count\", multiple=\"stack\")\n",
    "plt.xticks(rotation = \"vertical\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "5282d3e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "compensated_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          194,
          0
         ]
        },
        {
         "marker": {
          "color": "rgba(55, 128, 191, 0.6)",
          "line": {
           "color": "rgba(55, 128, 191, 1.0)",
           "width": 1
          }
         },
         "name": "negative",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          3367,
          53
         ]
        },
        {
         "marker": {
          "color": "rgba(50, 171, 96, 0.6)",
          "line": {
           "color": "rgba(50, 171, 96, 1.0)",
           "width": 1
          }
         },
         "name": "primary_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          95,
          0
         ]
        },
        {
         "marker": {
          "color": "rgba(128, 0, 128, 0.6)",
          "line": {
           "color": "rgba(128, 0, 128, 1.0)",
           "width": 1
          }
         },
         "name": "secondary_hypothyroid",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "f",
          "t"
         ],
         "y": [
          2,
          0
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"6d571536-f231-49a7-92e8-da7f3069076d\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"6d571536-f231-49a7-92e8-da7f3069076d\")) {                    Plotly.newPlot(                        \"6d571536-f231-49a7-92e8-da7f3069076d\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"compensated_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[194,0],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(55, 128, 191, 0.6)\",\"line\":{\"color\":\"rgba(55, 128, 191, 1.0)\",\"width\":1}},\"name\":\"negative\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[3367,53],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(50, 171, 96, 0.6)\",\"line\":{\"color\":\"rgba(50, 171, 96, 1.0)\",\"width\":1}},\"name\":\"primary_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[95,0],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(128, 0, 128, 0.6)\",\"line\":{\"color\":\"rgba(128, 0, 128, 1.0)\",\"width\":1}},\"name\":\"secondary_hypothyroid\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"f\",\"t\"],\"y\":[2,0],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('6d571536-f231-49a7-92e8-da7f3069076d');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df_copy['pregnant'],df_copy['Class']).iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "21e10f1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "hovertemplate": "label=%{label}<br>value=%{value}<extra></extra>",
         "labels": [
          "f",
          "t"
         ],
         "legendgroup": "",
         "name": "",
         "showlegend": true,
         "type": "pie",
         "values": [
          3658,
          53
         ]
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"c0311799-0fa1-4163-b663-cdd95620d887\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"c0311799-0fa1-4163-b663-cdd95620d887\")) {                    Plotly.newPlot(                        \"c0311799-0fa1-4163-b663-cdd95620d887\",                        [{\"domain\":{\"x\":[0.0,1.0],\"y\":[0.0,1.0]},\"hovertemplate\":\"label=%{label}<br>value=%{value}<extra></extra>\",\"labels\":[\"f\",\"t\"],\"legendgroup\":\"\",\"name\":\"\",\"showlegend\":true,\"values\":[3658,53],\"type\":\"pie\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('c0311799-0fa1-4163-b663-cdd95620d887');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pe.pie(names=df_copy['thyroid_surgery'].value_counts().index,values=df_copy['thyroid_surgery'].value_counts().values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8234435e",
   "metadata": {},
   "source": [
    "Observation :Overall 1.43 % of patients has taken thyoid sergery "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "5d11401e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'on_thyroxine', 'query_on_thyroxine',\n",
       "       'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery',\n",
       "       'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium',\n",
       "       'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH', 'T3', 'TT4', 'T4U',\n",
       "       'FTI', 'referral_source', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f338efa7",
   "metadata": {},
   "source": [
    "# Analysis of I131_treatment in thyroid treatment \n",
    "\n",
    "   *  I-131 treatment, also known as radioactive iodine therapy, is a common treatment for thyroid disorders such as hyperthyroidism and thyroid cancer. The treatment involves the administration of a dose of radioactive iodine, which is taken up by the thyroid gland and destroys the overactive thyroid tissue or cancerous cells.\n",
    "   * I-131 treatment also has a high success rate, with most patients experiencing complete remission of their condition after a single treatment.\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "2fd83eb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "hovertemplate": "label=%{label}<br>value=%{value}<extra></extra>",
         "labels": [
          "f",
          "t"
         ],
         "legendgroup": "",
         "name": "",
         "showlegend": true,
         "type": "pie",
         "values": [
          3652,
          59
         ]
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"870aad6a-c643-4136-98b6-899a74f542c1\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"870aad6a-c643-4136-98b6-899a74f542c1\")) {                    Plotly.newPlot(                        \"870aad6a-c643-4136-98b6-899a74f542c1\",                        [{\"domain\":{\"x\":[0.0,1.0],\"y\":[0.0,1.0]},\"hovertemplate\":\"label=%{label}<br>value=%{value}<extra></extra>\",\"labels\":[\"f\",\"t\"],\"legendgroup\":\"\",\"name\":\"\",\"showlegend\":true,\"values\":[3652,59],\"type\":\"pie\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('870aad6a-c643-4136-98b6-899a74f542c1');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pe.pie(names=df_copy['I131_treatment'].value_counts().index,values=df_copy['I131_treatment'].value_counts().values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b134c8",
   "metadata": {},
   "source": [
    "Observation : From overall patients 1.59% of have gone through the thyroid cancer treament which mainly affect for thyroid Diseasr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "fedb9048",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "f",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          2382,
          1125
         ]
        },
        {
         "marker": {
          "color": "rgba(55, 128, 191, 0.6)",
          "line": {
           "color": "rgba(55, 128, 191, 1.0)",
           "width": 1
          }
         },
         "name": "t",
         "orientation": "v",
         "text": "",
         "type": "bar",
         "x": [
          "F",
          "M"
         ],
         "y": [
          42,
          13
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#151516",
         "font": {
          "color": "#D9D9D9"
         }
        },
        "paper_bgcolor": "#151516",
        "plot_bgcolor": "#151516",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#D9D9D9"
         }
        },
        "xaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        },
        "yaxis": {
         "gridcolor": "#434343",
         "showgrid": true,
         "tickfont": {
          "color": "#C2C2C2"
         },
         "title": {
          "font": {
           "color": "#D9D9D9"
          },
          "text": ""
         },
         "zerolinecolor": "#666570"
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"ef0ec2fd-6370-4a24-adaa-6f0162f9a8fd\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';                                    if (document.getElementById(\"ef0ec2fd-6370-4a24-adaa-6f0162f9a8fd\")) {                    Plotly.newPlot(                        \"ef0ec2fd-6370-4a24-adaa-6f0162f9a8fd\",                        [{\"marker\":{\"color\":\"rgba(255, 153, 51, 0.6)\",\"line\":{\"color\":\"rgba(255, 153, 51, 1.0)\",\"width\":1}},\"name\":\"f\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[2382,1125],\"type\":\"bar\"},{\"marker\":{\"color\":\"rgba(55, 128, 191, 0.6)\",\"line\":{\"color\":\"rgba(55, 128, 191, 1.0)\",\"width\":1}},\"name\":\"t\",\"orientation\":\"v\",\"text\":\"\",\"x\":[\"F\",\"M\"],\"y\":[42,13],\"type\":\"bar\"}],                        {\"legend\":{\"bgcolor\":\"#151516\",\"font\":{\"color\":\"#D9D9D9\"}},\"paper_bgcolor\":\"#151516\",\"plot_bgcolor\":\"#151516\",\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"font\":{\"color\":\"#D9D9D9\"}},\"xaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"},\"yaxis\":{\"gridcolor\":\"#434343\",\"showgrid\":true,\"tickfont\":{\"color\":\"#C2C2C2\"},\"title\":{\"font\":{\"color\":\"#D9D9D9\"},\"text\":\"\"},\"zerolinecolor\":\"#666570\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('ef0ec2fd-6370-4a24-adaa-6f0162f9a8fd');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df_copy['sex'],df_copy['I131_treatment']).iplot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3817227d",
   "metadata": {},
   "source": [
    "Obseravtion : From male and female category Female has more count compared to Male of treatment of thyroid cancer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7185c5cc",
   "metadata": {},
   "source": [
    "# Analysis of query_hypothyroid "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "5d8b75f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "hovertemplate": "label=%{label}<br>value=%{value}<extra></extra>",
         "labels": [
          "f",
          "t"
         ],
         "legendgroup": "",
         "name": "",
         "showlegend": true,
         "type": "pie",
         "values": [
          3477,
          234
         ]
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"e110d0e5-479a-4943-90e0-fa6d8b9da787\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"e110d0e5-479a-4943-90e0-fa6d8b9da787\")) {                    Plotly.newPlot(                        \"e110d0e5-479a-4943-90e0-fa6d8b9da787\",                        [{\"domain\":{\"x\":[0.0,1.0],\"y\":[0.0,1.0]},\"hovertemplate\":\"label=%{label}<br>value=%{value}<extra></extra>\",\"labels\":[\"f\",\"t\"],\"legendgroup\":\"\",\"name\":\"\",\"showlegend\":true,\"values\":[3477,234],\"type\":\"pie\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('e110d0e5-479a-4943-90e0-fa6d8b9da787');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pe.pie(values=df_copy['query_hypothyroid'].value_counts(),names=df_copy['query_hyperthyroid'].value_counts().index)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6956aa6a",
   "metadata": {},
   "source": [
    "Observation :6.31 % of patients are uncertain about their Hypothyroidism they have to check their TSH level to ensure thyroid disease"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "aa715762",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "f    3677\n",
       "t      34\n",
       "Name: goitre, dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['goitre'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "79f218f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "f    3615\n",
       "t      96\n",
       "Name: tumor, dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['tumor'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "780be475",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='tumor', ylabel='goitre'>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(pd.crosstab(df_copy['goitre'],df_copy['tumor']),annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12a34ce3",
   "metadata": {},
   "source": [
    "Obervation : 1 patien has tumor as well goiter it is strongly affetcted by thyroid disease . 95 patients dont have goiter but they tumor it may cause to be patient of thyroid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db4de6e",
   "metadata": {},
   "source": [
    "# Analysis of Tumor in Males and Females "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "61f1e071",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='tumor', ylabel='sex'>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(pd.crosstab(df_copy['sex'],df_copy['tumor']),annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21a68c01",
   "metadata": {},
   "source": [
    "Obsearvation : out of all patients 85 female hav tumor and 9 male have tumor "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b38117a",
   "metadata": {},
   "source": [
    "# Analysis of pschyological factor in Detection of Thyoid "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fa7897f",
   "metadata": {},
   "source": [
    " * Psychological factors can play a role in thyroid detection and management in several ways.\n",
    " * Firstly, the symptoms of thyroid disorders can sometimes overlap with symptoms of depression, anxiety, or other mental health conditions.\n",
    " * Secondly, thyroid disorders can also impact mental health. For example, an overactive thyroid (hyperthyroidism) can cause symptoms such as irritability, nervousness, and difficulty concentrating, while an underactive thyroid (hypothyroidism) can cause symptoms such as depression, fatigue, and memory problems.\n",
    " * Thirdly, stress and other psychological factors can impact thyroid function. Chronic stress, for example, can lead to an increase in cortisol levels, which can affect thyroid hormone production and lead to imbalances. \n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "57e3ba1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "hovertemplate": "label=%{label}<br>value=%{value}<extra></extra>",
         "labels": [
          "f",
          "t"
         ],
         "legendgroup": "",
         "name": "",
         "showlegend": true,
         "type": "pie",
         "values": [
          3527,
          184
         ]
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "margin": {
         "t": 60
        },
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"fe04ddb2-ee22-4f91-b064-66fa9369914f\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"fe04ddb2-ee22-4f91-b064-66fa9369914f\")) {                    Plotly.newPlot(                        \"fe04ddb2-ee22-4f91-b064-66fa9369914f\",                        [{\"domain\":{\"x\":[0.0,1.0],\"y\":[0.0,1.0]},\"hovertemplate\":\"label=%{label}<br>value=%{value}<extra></extra>\",\"labels\":[\"f\",\"t\"],\"legendgroup\":\"\",\"name\":\"\",\"showlegend\":true,\"values\":[3527,184],\"type\":\"pie\"}],                        {\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('fe04ddb2-ee22-4f91-b064-66fa9369914f');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pe.pie(names=df_copy['psych'].value_counts().index,values=df_copy['psych'].value_counts().values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ab50edd",
   "metadata": {},
   "source": [
    "Observation :about 4.96% are suffering from psychological issues they may cause thyroid problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "9212e5fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='psych', ylabel='sex'>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(pd.crosstab(df_copy['sex'],df_copy['psych']),annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef4a42aa",
   "metadata": {},
   "source": [
    "Observation : 86 Female and 93 Males are suffering from psch problem "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e82f862",
   "metadata": {},
   "source": [
    "# Distribution of Numerical Features "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "03375695",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning:\n",
      "\n",
      "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x1080 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "columns = ['age','TSH','T3','TT4','T4U','FTI']\n",
    "\n",
    "plt.figure(figsize=(10,15),facecolor='white')\n",
    "plotnumber = 1\n",
    "\n",
    "for column in columns:\n",
    "    ax = plt.subplot(3,2,plotnumber)\n",
    "    sns.distplot(df_copy[column])\n",
    "    plt.xlabel(column,fontsize=10)\n",
    "    plotnumber+=1\n",
    "plt.show()\n",
    "     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6707eec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import skew"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "2e6089a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sex',\n",
       " 'on_thyroxine',\n",
       " 'query_on_thyroxine',\n",
       " 'on_antithyroid_medication',\n",
       " 'sick',\n",
       " 'pregnant',\n",
       " 'thyroid_surgery',\n",
       " 'I131_treatment',\n",
       " 'query_hypothyroid',\n",
       " 'query_hyperthyroid',\n",
       " 'lithium',\n",
       " 'goitre',\n",
       " 'tumor',\n",
       " 'hypopituitary',\n",
       " 'psych',\n",
       " 'referral_source',\n",
       " 'Class']"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_col = [i for i in df_copy.columns if df_copy[i].dtype == 'O']\n",
    "categorical_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "779dba25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['age', 'TSH', 'T3', 'TT4', 'T4U', 'FTI']"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Numerical_col = [i for i in df_copy.columns if df_copy[i].dtype != 'O']\n",
    "Numerical_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1b8c147e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>on_thyroxine</th>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <th>sick</th>\n",
       "      <th>pregnant</th>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <th>I131_treatment</th>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <th>...</th>\n",
       "      <th>tumor</th>\n",
       "      <th>hypopituitary</th>\n",
       "      <th>psych</th>\n",
       "      <th>TSH</th>\n",
       "      <th>T3</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI</th>\n",
       "      <th>referral_source</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41.0</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>1.30</td>\n",
       "      <td>2.5</td>\n",
       "      <td>125.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>109.0</td>\n",
       "      <td>SVHC</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23.0</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>4.10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>46.0</td>\n",
       "      <td>M</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>120.0</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70.0</td>\n",
       "      <td>F</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1.9</td>\n",
       "      <td>175.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70.0</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.72</td>\n",
       "      <td>1.2</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.87</td>\n",
       "      <td>70.0</td>\n",
       "      <td>SVI</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    age sex on_thyroxine query_on_thyroxine on_antithyroid_medication sick  \\\n",
       "0  41.0   F            f                  f                         f    f   \n",
       "1  23.0   F            f                  f                         f    f   \n",
       "2  46.0   M            f                  f                         f    f   \n",
       "3  70.0   F            t                  f                         f    f   \n",
       "4  70.0   F            f                  f                         f    f   \n",
       "\n",
       "  pregnant thyroid_surgery I131_treatment query_hypothyroid  ... tumor  \\\n",
       "0        f               f              f                 f  ...     f   \n",
       "1        f               f              f                 f  ...     f   \n",
       "2        f               f              f                 f  ...     f   \n",
       "3        f               f              f                 f  ...     f   \n",
       "4        f               f              f                 f  ...     f   \n",
       "\n",
       "  hypopituitary psych   TSH   T3    TT4   T4U    FTI  referral_source  \\\n",
       "0             f     f  1.30  2.5  125.0  1.14  109.0             SVHC   \n",
       "1             f     f  4.10  2.0  102.0   NaN    NaN            other   \n",
       "2             f     f  0.98  NaN  109.0  0.91  120.0            other   \n",
       "3             f     f  0.16  1.9  175.0   NaN    NaN            other   \n",
       "4             f     f  0.72  1.2   61.0  0.87   70.0              SVI   \n",
       "\n",
       "      Class  \n",
       "0  negative  \n",
       "1  negative  \n",
       "2  negative  \n",
       "3  negative  \n",
       "4  negative  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94003cdb",
   "metadata": {},
   "source": [
    "# Distribution of Numerical Features Before and After Transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "cd2a24ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['age'])\n",
    "plt.title(\"Origina\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.log(df_copy['age']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "cb965b91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['age', 'TSH', 'T3', 'TT4', 'T4U', 'FTI']"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Numerical_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "bd714824",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['TSH'])\n",
    "plt.title(\"Original\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.log(df_copy['TSH']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "111e09e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['T3'])\n",
    "plt.title(\"Original\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.sqrt(df_copy['T3']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "214c3282",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['TT4'])\n",
    "plt.title(\"Original\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.sqrt(df_copy['TT4']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "81be39c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['FTI'])\n",
    "plt.title(\"Original\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.sqrt(df_copy['FTI']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "c9e78f2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'After transformation')"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "sns.kdeplot(df_copy['T4U'])\n",
    "plt.title(\"Original\")\n",
    "plt.subplot(1,2,2)\n",
    "sns.kdeplot(np.log(df_copy['T4U']),color='red')\n",
    "plt.title(\"After transformation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fba648b",
   "metadata": {},
   "source": [
    "Observations:\n",
    "After Applying Transforamtion and Calculating the Skewness, we found best result for numerical features:\n",
    "* Age: LOG\n",
    "* TSH: LOG\n",
    "* T3: SQRT\n",
    "* TT4: SQRT\n",
    "* T4U: LOG\n",
    "* FTI: SQRT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "c51e9050",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3711, 23)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "aee1770b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'on_thyroxine', 'query_on_thyroxine',\n",
       "       'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery',\n",
       "       'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium',\n",
       "       'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH', 'T3', 'TT4', 'T4U',\n",
       "       'FTI', 'referral_source', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "105df2fa",
   "metadata": {},
   "source": [
    "# # Multivariate Analysis #"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "10c38fae",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\New folder\\anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning:\n",
      "\n",
      "Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='TT4', ylabel='FTI'>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(df_copy['TT4'],df_copy['FTI'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "a27bab84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x7200 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#lets see the outliers in dataset \n",
    "numeric_features = [feature for feature in df_copy.columns if df_copy[feature].dtype != 'O']\n",
    "\n",
    "plt.figure(figsize=(15, 100))\n",
    "for i, col in enumerate(numeric_features):\n",
    "    plt.subplot(60, 3, i+1)\n",
    "    sns.boxplot(x=df_copy[col])\n",
    "    plt.xlabel(col, weight='bold')\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "c2b57a12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df_copy.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "ca02ff0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'on_thyroxine', 'query_on_thyroxine',\n",
       "       'on_antithyroid_medication', 'sick', 'pregnant', 'thyroid_surgery',\n",
       "       'I131_treatment', 'query_hypothyroid', 'query_hyperthyroid', 'lithium',\n",
       "       'goitre', 'tumor', 'hypopituitary', 'psych', 'TSH', 'T3', 'TT4', 'T4U',\n",
       "       'FTI', 'referral_source', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "8bb32c9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Since it is of no use for analysing thyroid disease so we can drop it "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "9f86c89b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy.drop('referral_source',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "fd1fea84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>on_thyroxine</th>\n",
       "      <th>query_on_thyroxine</th>\n",
       "      <th>on_antithyroid_medication</th>\n",
       "      <th>sick</th>\n",
       "      <th>pregnant</th>\n",
       "      <th>thyroid_surgery</th>\n",
       "      <th>I131_treatment</th>\n",
       "      <th>query_hypothyroid</th>\n",
       "      <th>...</th>\n",
       "      <th>goitre</th>\n",
       "      <th>tumor</th>\n",
       "      <th>hypopituitary</th>\n",
       "      <th>psych</th>\n",
       "      <th>TSH</th>\n",
       "      <th>T3</th>\n",
       "      <th>TT4</th>\n",
       "      <th>T4U</th>\n",
       "      <th>FTI</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41.0</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>1.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>125.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>109.0</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23.0</td>\n",
       "      <td>F</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    age sex on_thyroxine query_on_thyroxine on_antithyroid_medication sick  \\\n",
       "0  41.0   F            f                  f                         f    f   \n",
       "1  23.0   F            f                  f                         f    f   \n",
       "\n",
       "  pregnant thyroid_surgery I131_treatment query_hypothyroid  ... goitre tumor  \\\n",
       "0        f               f              f                 f  ...      f     f   \n",
       "1        f               f              f                 f  ...      f     f   \n",
       "\n",
       "  hypopituitary psych  TSH   T3    TT4   T4U    FTI     Class  \n",
       "0             f     f  1.3  2.5  125.0  1.14  109.0  negative  \n",
       "1             f     f  4.1  2.0  102.0   NaN    NaN  negative  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "f0452c87",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Finding corelation of categorical features with target column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "5c1151bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sex',\n",
       " 'on_thyroxine',\n",
       " 'query_on_thyroxine',\n",
       " 'on_antithyroid_medication',\n",
       " 'sick',\n",
       " 'pregnant',\n",
       " 'thyroid_surgery',\n",
       " 'I131_treatment',\n",
       " 'query_hypothyroid',\n",
       " 'query_hyperthyroid',\n",
       " 'lithium',\n",
       " 'goitre',\n",
       " 'tumor',\n",
       " 'hypopituitary',\n",
       " 'psych',\n",
       " 'referral_source',\n",
       " 'Class']"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#categorical_col.remove('Class')\n",
    "#categorical_col.remove('referral_source')\n",
    "categorical_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "949f1825",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.stats as  stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "9e6cfec2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chi-square test of independence for sex\n",
      "Chi-square statistic: 11.410141468107955\n",
      "P-value: 0.009702764404501156\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.27256597e+02 2.23345536e+03 6.19270073e+01 1.36103313e+00]\n",
      " [5.97434026e+01 1.04854464e+03 2.90729927e+01 6.38966873e-01]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for on_thyroxine\n",
      "Chi-square statistic: 30.81005520697033\n",
      "P-value: 9.320384698267207e-07\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.69743465e+02 2.99238480e+03 8.31218001e+01 1.74993263e+00]\n",
      " [2.42565346e+01 4.27615198e+02 1.18781999e+01 2.50067367e-01]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for query_on_thyroxine\n",
      "Chi-square statistic: 1.4012510105268492\n",
      "P-value: 0.7052415135771981\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.91386149e+02 3.37392078e+03 9.37200216e+01 1.97305309e+00]\n",
      " [2.61385071e+00 4.60792239e+01 1.27997844e+00 2.69469146e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for on_antithyroid_medication\n",
      "Chi-square statistic: 1.906369105285771\n",
      "P-value: 0.5920656803842737\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.91804365e+02 3.38129345e+03 9.39248181e+01 1.97736459e+00]\n",
      " [2.19563460e+00 3.87065481e+01 1.07518189e+00 2.26354082e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for sick\n",
      "Chi-square statistic: 5.492219081068567\n",
      "P-value: 0.1391047438767816\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.86315279e+02 3.28452708e+03 9.12368634e+01 1.92077607e+00]\n",
      " [7.68472110e+00 1.35472918e+02 3.76313662e+00 7.92239289e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for pregnant\n",
      "Chi-square statistic: 4.574988489539869\n",
      "P-value: 0.205698224355036\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.91229318e+02 3.37115602e+03 9.36432229e+01 1.97143627e+00]\n",
      " [2.77068176e+00 4.88439774e+01 1.35677715e+00 2.85637295e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for thyroid_surgery\n",
      "Chi-square statistic: 3.2457092995287775\n",
      "P-value: 0.3552706582435053\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.91229318e+02 3.37115602e+03 9.36432229e+01 1.97143627e+00]\n",
      " [2.77068176e+00 4.88439774e+01 1.35677715e+00 2.85637295e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for I131_treatment\n",
      "Chi-square statistic: 0.19855015766460263\n",
      "P-value: 0.9778230118963299\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.90915656e+02 3.36562652e+03 9.34896254e+01 1.96820264e+00]\n",
      " [3.08434384e+00 5.43734842e+01 1.51037456e+00 3.17973592e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for query_hypothyroid\n",
      "Chi-square statistic: 32.07164412324175\n",
      "P-value: 5.054636623257259e-07\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.81767179e+02 3.20434923e+03 8.90097009e+01 1.87388844e+00]\n",
      " [1.22328213e+01 2.15650768e+02 5.99029911e+00 1.26111560e-01]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for query_hyperthyroid\n",
      "Chi-square statistic: 1.7880331195765922\n",
      "P-value: 0.6175425192517998\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.81767179e+02 3.20434923e+03 8.90097009e+01 1.87388844e+00]\n",
      " [1.22328213e+01 2.15650768e+02 5.99029911e+00 1.26111560e-01]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for lithium\n",
      "Chi-square statistic: 0.48676194835195263\n",
      "P-value: 0.9217899786367105\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.93059014e+02 3.40341148e+03 9.45392078e+01 1.99029911e+00]\n",
      " [9.40986257e-01 1.65885206e+01 4.60792239e-01 9.70088925e-03]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for goitre\n",
      "Chi-square statistic: 2.9197329058299824\n",
      "P-value: 0.40416706534130475\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.92222582e+02 3.38866613e+03 9.41296147e+01 1.98167610e+00]\n",
      " [1.77741849e+00 3.13338723e+01 8.70385341e-01 1.83239019e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for tumor\n",
      "Chi-square statistic: 0.3401654303837905\n",
      "P-value: 0.9523056071491356\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.88981407e+02 3.33152789e+03 9.25424414e+01 1.94826192e+00]\n",
      " [5.01859337e+00 8.84721099e+01 2.45755861e+00 5.17380760e-02]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for hypopituitary\n",
      "Chi-square statistic: 0.08511065399347424\n",
      "P-value: 0.9935622698106221\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.93947723e+02 3.41907842e+03 9.49744004e+01 1.99946106e+00]\n",
      " [5.22770143e-02 9.21584479e-01 2.55995688e-02 5.38938292e-04]]\n",
      "-------------------------------------------------------------------------\n",
      "Chi-square test of independence for psych\n",
      "Chi-square statistic: 5.603512420835704\n",
      "P-value: 0.1325768590472525\n",
      "Degrees of freedom: 3\n",
      "Expected values: [[1.84381029e+02 3.25042846e+03 9.02896793e+01 1.90083535e+00]\n",
      " [9.61897063e+00 1.69571544e+02 4.71032067e+00 9.91646456e-02]]\n",
      "-------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for feature in ['sex','on_thyroxine','query_on_thyroxine','on_antithyroid_medication','sick','pregnant','thyroid_surgery',\n",
    " 'I131_treatment','query_hypothyroid','query_hyperthyroid','lithium','goitre','tumor','hypopituitary','psych']:\n",
    "    contingency_table = pd.crosstab(df_copy[feature], df_copy['Class'])\n",
    "    chi2, p, dof, expected = stats.chi2_contingency(contingency_table)\n",
    "    print('Chi-square test of independence for', feature)\n",
    "    print('Chi-square statistic:', chi2)\n",
    "    print('P-value:', p)\n",
    "    print('Degrees of freedom:', dof)\n",
    "    print('Expected values:', expected)\n",
    "    print(\"-------------------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "4092809d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy.to_csv(\"Thyroid_EDA.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3cbb69b8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
